A stochastic approach to hotel revenue management considering multiple-day stays

被引:7
|
作者
Liu, Shuqin
Lai, Kin Keung
Dong, Jichang
Wang, Shou-Yang
机构
[1] City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
[2] Hunan Univ, Coll Business Adm, Hunan 410082, Peoples R China
[3] Beihang Univ, Sch Econ & Management, Beijing 100083, Peoples R China
[4] Chinese Acad Sci, Grad Sch, Sch Management, Beijing 100080, Peoples R China
[5] Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
[6] Univ Tsukuba, Grad Sch Syst & Informat Engn, Tsukuba, Ibaraki 3058573, Japan
关键词
revenue management; stochastic programming; semi-absolute deviation;
D O I
10.1142/S021962200600212X
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a stochastic optimization model for hotel revenue management with multiple-day stays under an uncertain environment. Since a decision maker may face several scenarios when renting out rooms, we use a semi-absolute deviation model to measure the risk of hotel revenue, and only consider the risk of falling below the expected revenue. The method proposed in this paper can be changed to a linear programming model by applying linearization techniques. Some examples are presented to illustrate the efficiency of this method.
引用
收藏
页码:545 / 556
页数:12
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